Cannabinoids versus placebo for pain: A systematic review with meta-analysis and Trial Sequential Analysis

Objectives To assess the benefits and harms of cannabinoids in participants with pain. Design Systematic review of randomised clinical trials with meta-analysis, Trial Sequential Analysis, and the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach. Data sources The Cochrane Library, MEDLINE, Embase, Science Citation Index, and BIOSIS. Eligibility criteria for selecting studies Published and unpublished randomised clinical trials comparing cannabinoids versus placebo in participants with any type of pain. Main outcome measures All-cause mortality, pain, adverse events, quality of life, cannabinoid dependence, psychosis, and quality of sleep. Results We included 65 randomised placebo-controlled clinical trials enrolling 7017 participants. Fifty-nine of the trials and all outcome results were at high risk of bias. Meta-analysis and Trial Sequential Analysis showed no evidence of a difference between cannabinoids versus placebo on all-cause mortality (RR 1.20; 98% CI 0.85 to 1.67; P = 0.22). Meta-analyses and Trial Sequential Analysis showed that cannabinoids neither reduced acute pain (mean difference numerical rating scale (NRS) 0.52; 98% CI -0.40 to 1.43; P = 0.19) or cancer pain (mean difference NRS -0.13; 98% CI -0.33 to 0.06; P = 0.1) nor improved quality of life (mean difference -1.38; 98% CI -11.81 to 9.04; P = 0.33). Meta-analyses and Trial Sequential Analysis showed that cannabinoids reduced chronic pain (mean difference NRS -0.43; 98% CI -0.72 to -0.15; P = 0.0004) and improved quality of sleep (mean difference -0.42; 95% CI -0.65 to -0.20; P = 0.0003). However, both effect sizes were below our predefined minimal important differences. Meta-analysis and Trial Sequential Analysis indicated that cannabinoids increased the risk of non-serious adverse events (RR 1.20; 95% CI 1.15 to 1.25; P < 0.001) but not serious adverse events (RR 1.18; 98% CI 0.95 to 1.45; P = 0.07). None of the included trials reported on cannabinoid dependence or psychosis. Conclusions Cannabinoids reduced chronic pain and improved quality of sleep, but the effect sizes are of questionable importance. Cannabinoids had no effects on acute pain or cancer pain and increased the risks of non-serious adverse events. The harmful effects of cannabinoids for pain seem to outweigh the potential benefits.


Introduction
Pain is the most commonly reported symptom in the general population and medical settings [1][2][3]. Persistent or chronic pain is a major universal health problem [4], prompting the WHO to endorse a global campaign against pain [5]. Pain has been associated with lower degree of health-related quality of life and may lead to psychosocial distress, insomnia, and depressive symptoms [6][7][8][9][10][11][12][13][14].

Cannabinoids
Cannabinoids have lately emerged as a potential alternative to other analgesics, e.g., opioids for the treatment of pain [15]. Cannabinoids are most commonly consumed via smoked, inhaled vapour, or oral routes of administration [16]. Sublingual administration is used for some medical cannabis preparations (e.g., nabiximol).
The endocannabinoid system consists of two types of cannabinoid receptors in the human body, type I and type II [17]. Cannabinoid receptor type I are most abundant in the central nervous system, especially in areas stimulating nociception and short-term memory, and in the basal ganglia. Cannabinoid receptor type II is mostly found in the periphery, often in conjunction with immune cells, but may appear in the central nervous system predominantly in association with microcytes during inflammation [17].
These receptors is thought to suppress the pain stimulus through different mechanisms [18]. Neurochemical, behavioral, and electrophysiological studies all demonstrated the modulation of inflammatory nociception through cannabinoid receptor type II activation [19].

Methods
The objective of our systematic review was to assess the benefits and harms of cannabinoids versus placebo or no intervention for participants with any type of pain (acute and chronic pain, cancer pain, or any other types of pain). Our methodology is described in detail in our protocol published prior to conducting the literature search [33].
In short, we carried out this systematic review following the recommendations of the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines [34]. We included all randomised clinical trials comparing cannabinoids versus placebo or no intervention for participants with any type of pain. Two authors (JB, SKK) independently searched for trials identified prior to January 2022 see 'Supplement 1 in S1 File' for a detailed list of databases and 'Supplement 2 in S1 File' for the search strategy. We included randomised clinical trials regardless of trial design, setting, publication status, year, language, and reporting of outcomes. Four authors (JB, SKK, JBF, and MM) working in pairs independently extracted data and assessed the risks of bias in included trials. We contacted trial authors by email if data were unclear or missing. Disagreements were resolved through discussion or by consulting a third author (JCJ).

Outcomes Primary outcomes.
• All-cause mortality • Pain assessment on visual analogue scale (VAS) or numerical rating scale (NRS) • Proportion of participants with one or more serious adverse events. Serious adverse events were defined as any untoward medical occurrence that resulted in death; was life threatening; was persistent or led to significant disability, hospitalisation, or prolonged hospitalisation [35]. As we expected the trialists' reporting of serious adverse events to be heterogeneous and not strictly according to the International Conference on Harmonisation -Good Clinical Practice (ICH-GCP) recommendations, we included the event as a serious adverse if the trialists either: (1) used the term 'serious adverse event' but did not refer to ICH-GCP, or (2) reported the proportion of participants with an event we considered fulfils the ICH-GCP definition. If several of such events were reported then we choose the highest proportion reported in each trial • Quality of life measured on any valid (published validation) continuous scale Secondary outcomes.
• Cannabinoid dependence (as defined by trialists) • Psychosis (as defined by trialists) • Proportion of participants with one or more adverse event not considered to be serious • Quality of sleep measured on any valid (published validation) continuous scale Exploratory outcomes.
• Each type of serious adverse event separately • Each type of adverse event not considered serious separately • Twenty-four hours morphine consumption (as defined by trialists) • Physical function (as defined by trialists) • Depressive symptoms (e.g., Hamilton Depression Rating Scale) Adverse events were included in our analysis regardless of whether it was defined as an outcome by the trialists. For all outcomes, we used the trial results reported at maximal follow-up. Patient and public involvement. We conducted email correspondence with several patient associations in Denmark to select the most patient-relevant outcomes. The associations were the Danish Diabetes Association, the Danish Rheumatism Association, the Danish Multiple Sclerosis Society, and the Danish Cancer Society.
Sub-group analyses. We pre-defined subgroup analyses for our primary outcomes assessing risk of bias, risk of vested interests, type of pain, type of chronic pain, and type of cannabinoids used [33].
Assessment of risk of bias. We assessed risk of bias according to the Cochrane Handbook for Systematic Reviews of Interventions 5.1 [36]. We evaluated the risk of bias in the domains 'random sequence generation', 'allocation concealment', 'blinding of participants and treatment providers', 'blinding of outcome assessment, 'incomplete outcome data', and 'selective outcome reporting'. We used these domains to classify the included trials as being at overall low risk of bias or at overall high risk of bias as described in our protocol [33].
The domains 'blinding of outcome assessment', 'incomplete outcome data', and 'selective outcome reporting' were further assessed separately for each outcome result.
Assessment of effect. We calculated risk ratios (RRs) with 95% and 98% confidence intervals (CIs) for our continuous and dichotomous outcomes (see "Assessment of statistical and clinical significance"). For our dichotomous outcomes we used the conventional direction with RR > 1.0 representing higher risk in the experimental intervention group.
We calculated mean differences (MDs) and standardised mean differences (SMDs) for our continuous outcomes. For pain assessment, we used the numerical rating scale to measure the mean difference between groups [37]. Visual analog scale (VAS) (0 to 100) was converted into the numerical rating scale (NRS) (0 to 10) by dividing with 10 [37].
Assessment of heterogeneity. We investigated forest plots to visually assess any sign of heterogeneity. We secondly assessed the presence of statistical heterogeneity by Chi 2 test (threshold P < 0.10) and measured the quantities of heterogeneity by I 2 statistic and tau (τ) 2 statistic [38,39]. We also investigated heterogeneity through subgroup analyses. Ultimately, we decided whether the assessment of heterogeneity showed that meta-analysis should be avoided [36].
Assessment of reporting biases. We used funnel plots to assess reporting bias, although it should be noted that funnel plots assess small-study effects [ [43,45]. We primarily reported the more conservative point estimate of the two and the less conservative result as a sensitivity analysis [46]. To control random errors when analysing our primary outcomes, we adjusted the threshold for statistical significance using the procedure suggested by Jakobsen and colleagues [46]. We used four primary outcomes and therefore considered a P-value of 0.02 as the threshold for statistical significance [46]. When analysing secondary and exploratory outcomes, we considered a P-value of 0.05 as the threshold for statistical significance as these outcomes were considered hypothesis-generating only [46].
We used Trial Sequential Analysis (TSA) to control for the risks of random errors [47]. Traditional meta-analysis runs the risk of random errors due to sparse data and repetitive testing of accumulating data when updating reviews. We wished to control the risks of type I errors and type II errors [46]. By conducting TSA on the outcomes, we could calculate the required information size, i.e., the number of participants needed in a meta-analysis to detect or reject our anticipated intervention effects [46].
For dichotomous outcomes, we estimated the required information size based on the observed proportion of participants with an outcome in the control group, a relative risk reduction of 20% in the experimental group, an alpha of 2.0%, a beta of 10%, and the diversity suggested by the trials in the meta-analysis. For the outcome pain assessment on VAS or NRS, we used an analgesic effect equivalent to 10 mm on VAS or 1 point on NRS. For the outcome 24-hour morphine consumption we used an effect equivalent to at least 5 mg morphine. For the remaining continuous outcomes, we used the observed standard deviation (SD), a mean difference of the observed SD/2, an alpha of 2.0% for our primary and secondary outcomes, a beta of 10%, and the diversity suggested by the trials in the meta-analysis [33]. The above-mentioned intervention effects used in the TSA were also predefined as the minimal important differences (MIDs) of the review [33].
We used a 'best-worst case' and a 'worst-best case' sensitivity analysis to assess the impact of missing data (incomplete outcome data bias) [36]. We used the Grading of Recommendations Assessment, Development and Evaluation (GRADE) to assess the certainty of the evidence [48, 49].

Results
Our literature search identified 5766 records. After removing duplicates, 4302 records remained. We excluded 4196 records based on title or abstract. We excluded another 41 records based on the full texts (Fig 1). We included a total of 65 clinical trials randomising 7017 participants .
All 65 trials compared cannabinoids versus placebo. The mean age of included participants was 50.4 years ranging from a mean of 20.7 years [74] to 63.7 years [63] (see Table 1 for more details).
The participants were included in the trials based on the different pain diagnoses. Fortyfour trials randomised 4306 participants with chronic pain (34 trials in neuropathic pain, and 10 trials in chronic nociceptive pain); 9 trials randomised 1681 participants with cancer pain; 10 trials randomised 965 participants with acute pain; and 2 trials randomised 65 participants with fibromyalgia-related pain.
Length of maximum follow-up of the included trials varied between 7 hours [71] and 16 weeks [92] with a mean length of follow-up of 7.3 weeks.  Only 35 of the 65 trials provided data that could be included in our meta-analysis. The primary reason that trial data could not be included in the meta-analyses was that the trials were designed as cross-over trials and that they did not provide data at the end of the first phase. These trials are described qualitatively in the paragraph 'Trials not contributing with data in our meta-analyses'. Fifty-nine of the 65 included trials were at high risk of bias, see 'Supplement 4 in S1 File' and 'S4 File' for more information on bias assessment.

Primary outcomes
All-cause mortality. Seven trials randomising 2073 participants reported on all-cause mortality. Meta-analysis showed no evidence of a difference between cannabinoids versus placebo (RR 1.20; 98% CI 0.85 to 1.67; P = 0.22; low certainty of evidence; S1 Fig in S1 File). Visual inspection of the forest plot, I 2 -statistic (I 2 = 7%), and tau 2 statistic (τ 2 = 0.01; τ = 0.1) indicated low heterogeneity. TSA showed that there was not enough information to confirm or reject that cannabinoids versus placebo increased the risk of all-cause mortality by 20% or more (S2 Fig in  S1 File). We assessed this outcome result at high risk of bias, see 'Supplement 4 in S1 File' and S3 and S4 Figs in S1 File. Test for interaction showed no evidence of a difference when comparing trials at high risk of bias to trials at low risk of bias (P = 0.87) (S5 Fig in S1 File); trials at risk of vested interests to trials at no risk of vested interests (P = 0.87) (S6 Fig in S1 File); trials assessing different types of pain, i.e., cancer pain and chronic pain (P = 0.43) (S7 Fig in S1 File); trials comparing the effects of different types of cannabinoids (P = 0.78) (S8 Fig in S1 File). The remaining planned subgroup analyses were not possible to conduct due to lack of relevant data.
Pain. Twenty-six trials randomising 4110 participants assessed pain using either VAS (8 trials) or NRS (18 trials). We converted all pain measures to NRS as described in the 'Methods' section.
The visual inspection of the forest plot and test for subgroup difference (P = 0.02), showed that the effects of cannabinoids seemed to differ between trials randomising participants with acute pain, cancer pain, and chronic pain (S9 Fig in S1 File). It was therefore not justifiable to meta-analyse the results of trials including the different types of pain. Hence, we chose to report results separately for each group of trials (acute pain; cancer pain; and chronic pain).
Acute pain. Four trials randomising 530 participants suffered from acute pain. Meta-analysis showed no evidence of a difference between cannabinoids versus placebo (mean difference NRS 0.52; 98% CI -0.40 to 1.43; P = 0.19; very low certainty of evidence; S10 Fig in S1 File). Visual inspection of the forest plot, I 2 -statistic (I 2 = 90%), and tau 2 statistic (τ 2 = 0.67, τ = 0.82) indicated high heterogeneity that could not be resolved. TSA showed that we had not enough information to confirm or reject that cannabinoids versus placebo reduced acute pain (S11 Fig  in S1 File). We assessed this outcome result at high risk of bias, see 'Supplement 4 in S1 File'.
Test of interaction showed evidence of a difference when comparing trials at high risk of bias to trials at low risk of bias (P = 0.035) (S12 Fig in S1 File). When trials at low risk of bias and trials at high risk of bias were analysed separately we found no evidence of a difference between cannabinoids versus placebo (S12 Fig in S1 File).
Test of interaction showed no evidence of a difference when comparing trials at risk of vested interests to trials at no risk of vested interests (P = 0.25) (S13 Fig in S1 File).
All remaining planned subgroup analyses were not possible to conduct due to lack of relevant data.
A post-hoc subgroup analysis comparing trials with long-term follow-up to trials with short-term follow-up showed no evidence of a difference (P = 0.10) (S14 Fig in S1 File).
Cancer pain. Six trials randomising 1550 participants suffered from cancer pain. Metaanalysis showed no evidence of a difference between cannabinoids versus placebo (mean difference NRS -0.13; 98% CI -0.33 to 0.06; P = 0.1; low certainty of evidence; S15 Fig in S1 File). Visual inspection of the forest plot, I 2 -statistic (I 2 = 2%), and tau 2 statistic (τ 2 = 0.00) indicated low heterogeneity. TSA showed that there was enough information to reject that cannabinoids versus placebo reduced cancer pain (S16 Fig in S1 File). We assessed this outcome result as high risk of bias, see 'Supplement 4 in S1 File'.
Test of interaction showed no evidence of a difference when comparing trials assessing the effects of different types of cannabinoids (P = 0.71) (S17 Fig in S1 File).
All remaining planned subgroup analyses were not possible to conduct due to lack of relevant data.
A post-hoc subgroup analysis comparing trials with long-term follow-up to trials with short-term follow-up showed no evidence of a difference (P = 0.06) (S18 Fig in S1 File).
Chronic pain. Sixteen trials randomising 2030 participants suffered from chronic pain. Meta-analysis showed that cannabinoids reduced chronic pain, but the effect size was below the predefined MID and the MID was not included in the 98% confidence interval (mean difference NRS -0.43; 98% CI -0.72 to -0.15; P = 0.0004; low certainty of evidence; Fig 2, S19 Fig in S1 File). Visual inspection of the forest plot, I 2 -statistic (I 2 = 64%), and tau 2 statistic (τ 2 = 0.11) indicated moderate heterogeneity that could not be resolved. TSA showed that there was enough information to confirm that cannabinoids versus placebo reduced chronic pain with a statistically significant effect (S20 Fig in S1 File). We assessed this outcome result as high risk of bias, see 'Supplement 4 in S1 File'.
Test for interaction showed no evidence of a difference when comparing trials at high risk of bias to trials at low risk of bias (P = 0.31) (S21 Fig in S1 File); and trials at risk of vested interests to trials at no risk of vested interests (P = 0.57) (S22 Fig in S1 File). Test for interaction showed evidence of a difference when comparing trials assessing different types of chronic pain, i.e., neuropathic pain (including central, peripheral, and mixed), fibromyalgia, and visceral nociceptive pain (P = 0.01) (S23 Fig in S1 File); and trials comparing the effects of different types of cannabinoids (P < 0.001) (S24 Fig in S1 File).
The funnel plot showed no clear signs of small-study effects (S25 Fig in S1 File).
A post-hoc subgroup analysis comparing trials with long-term follow-up to trials with short-term follow-up showed no evidence of a difference (P = 0.59) (S26 Fig in S1 File).
Serious adverse events. Eighteen trials randomising 3980 participants reported serious adverse events. Meta-analysis showed no evidence of a difference between cannabinoids versus placebo (RR 1.18; 98% CI 0.95 to 1.45; P = 0.07; low certainty of evidence; Fig 3, S27 Fig in  S1 File). Visual inspection of the forest plot, I 2 -statistic (I 2 = 0%), and tau 2 statistic (τ 2 = 0.00) indicated low heterogeneity. TSA showed that there was not enough information to confirm or reject that cannabinoids versus placebo increased the risk of serious adverse events by 20% or more (S28 Fig in S1 File). We assessed this outcome result at high risk of bias, see 'Supplement 4 in S1 File' and S29 and S30 Figs in S1 File. Test for interaction showed no evidence of a difference when comparing trials at risk of vested interests to trials at no risk of vested interests (P = 0.97) (S31 Fig in S1 File); trials assessing different types of pain, i.e. acute pain, cancer pain and chronic pain (P = 0.96) (S32  Fig in S1 File); trials assessing different types of chronic pain, i.e., neuropathic pain (including central and peripheral) and nociceptive pain (P = 0.16) (S33 Fig in S1 File); and trials comparing the effects of different types of cannabinoids (P = 0.79) (S34 Fig in S1 File).
The remaining planned subgroup analyses were not possible to conduct due to lack of relevant data.
The funnel plot showed no clear signs of small-study effects (S35 Fig in S1 File).
When analysing each specific serious adverse event, cannabinoids did not seem to increase or decrease the risk of any single serious adverse events compared with placebo, see 'S2 File'.
Quality of life. Only four trials randomising 548 participants assessed quality of life using either EuroQol 5-D (3 trials) or EORTC-QLQC30 (1 trial). Meta-analysis showed no evidence of a difference between cannabinoids versus placebo (mean difference -1.38; 98% CI -11.8 to

PLOS ONE
9.04; P = 0.75; very low certainty of evidence; S36 Fig in S1 File). Visual inspection of the forest plot, I 2 -statistic (I 2 = 86%), and tau 2 statistic (τ 2 = 61.98, τ = 7.87) indicated high heterogeneity which could not be resolved. TSA showed that there was not enough information to confirm or reject that cannabinoids versus placebo improved quality of life (S37 Fig in S1 File). We assessed this outcome result as high risk of bias, see 'Supplement 4 in S1 File'.
Test for interaction showed no evidence of a difference when comparing trials assessing different types of pain, i.e., cancer pain and chronic pain (P = 0.33) (S38 Fig in S1 File) and trials comparing the effects of different types of cannabinoids (P = 0.56) (S39 Fig in S1 File).
All remaining planned subgroup analyses were not possible to conduct due to lack of relevant data.

Secondary outcomes
Dependence and psychosis. None of the included randomised clinical trials reported results on the outcomes 'dependence' or 'psychosis' that could be analysed through a metaanalysis.
Non-serious adverse events. Twenty-nine trials randomising 5536 participants reported non-serious adverse events. Meta-analysis showed evidence of a harmful effect of cannabinoids (RR 1.20; 95% CI 1.15 to 1.25; P < 0.001; very low certainty of evidence; Fig 4, S40 Fig in S1  File). The number needed to harm (NNH) was seven. Visual inspection of the forest plot, I 2statistic (I 2 = 27%), and tau 2 statistic (τ 2 = 0.00) indicated low heterogeneity. TSA showed that there was enough information to confirm that cannabinoids versus placebo increased the risk of non-serious adverse events by 20% or more (S41 Fig in S1 File). We assessed this outcome result at high risk of bias, see 'Supplement 4 in S1 File' and S42 and S43 Figs in S1 File.
The funnel plot showed signs of small-study effects (S44 Fig in S1 File).
When analysing each specific non-serious adverse event, cannabinoids seemed to increase the risk of five non-serious adverse events versus placebo, see 'S3 File'. These were 'dizziness', 'fatigue', 'vertigo', 'nervous system disorders', and 'gastrointestinal disorder'.
Cannabinoids did not seem to decrease the risk of any non-serious adverse events. Quality of sleep. Seventeen trials randomising 3291 participants assessed quality of sleep using numerical rating scale (NRS). Meta-analysis showed that cannabinoids versus placebo improved quality of sleep, but the effect size was below the predefined MID and the MID was excluded in the confidence interval (mean difference NRS -0.42; 95% CI -0.65 to -0.20; P = 0.0003; low certainty of evidence; Fig 5, S45 Fig in S1 File). Visual inspection of the forest plot, I 2 -statistic (I 2 = 74%), and tau 2 statistic (τ 2 = 0.15) indicated moderate heterogeneity that could not be resolved. TSA showed that there was enough information to confirm that cannabinoids versus placebo improved quality of sleep with a statistically significant effect (S46 Fig  in S1 File). We assessed this outcome result at high risk of bias, see 'Supplement 4 in S1 File'.
The funnel plot showed no clear signs of small-study effects (S47 Fig in S1 File).

Exploratory outcomes
Twenty-four hours morphine consumption. Six trials randomising 1546 participants assessed 24-hours morphine consumption. Meta-analysis showed no evidence of a difference between cannabinoids versus placebo (mean difference -0.01; 95% CI -1.60 to 1.59; P = 0.99; low certainty of evidence; S48 Fig in S1 File). Visual inspection of the forest plot and I 2 -statistic (I 2 = 21%) and tau 2 statistic (τ 2 = 29.78, τ = 5.46) indicated low heterogeneity. TSA showed that there was enough information to reject that cannabinoids versus placebo reduced 24-hours morphine consumption by five mg morphine equivalents or more (S49 Fig in S1  File). We assessed this outcome result at high risk of bias, see 'Supplement 4 in S1 File'. Physical function (measured by activities of daily living). Three trials randomising 320 participants assessed ability to perform activities of daily living (ADL) using Barthel Index. Meta-analysis showed no evidence of a difference between cannabinoids versus placebo (mean difference 0.21; 95% CI -0.10 to 0.51; P = 0.18; very low certainty of evidence; S50 Fig in S1  File). Visual inspection of the forest plot and I 2 -statistic (I 2 = 0%) and tau 2 statistic (τ 2 = 0.00) indicated low heterogeneity. TSA could not be performed due to inadequate information size. We assessed this outcome result at high risk of bias, see 'Supplement 4 in S1 File'.

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Depressive symptoms. Five trials randomising 651 participants assessed depressive symptoms using either HADS-D (3 trials), MADRS (1 trial) or BDI-II (1 trial). Meta-analysis showed no evidence of a difference between cannabinoids versus placebo (mean difference -0.03; 95% CI -0.12 to 0.06; P = 0.49; low certainty of evidence; S51 Fig in S1 File). Visual inspection of the forest plot and I 2 -statistic (I 2 = 0%) and tau 2 statistic (τ 2 = 0.00) indicated low heterogeneity. TSA showed that there was enough information to reject that cannabinoids versus placebo improved depressive symptoms (S52 Fig in S1 File). We assessed this outcome result at high risk of bias, see 'Supplement 4 in S1 File'.

Discussion
The objective of this review was to assess the beneficial and harmful effects of cannabinoids in any dose, formulation, and duration versus placebo or no intervention for participants with any type of pain.
Meta-analysis and TSA showed no evidence of a difference between cannabinoids versus placebo on all-cause mortality, serious adverse events, and quality of life. Meta-analyses showed that cannabinoids compared with placebo reduced chronic pain (in particular central and peripheral neuropathic pain) and improved quality of sleep, but both effect sizes were below our predefined minimal important differences and the minimal important differences were excluded by both confidence intervals. Meta-analyses and TSA showed that cannabinoids increased the risks of non-serious adverse events, which corresponds to a number needed to harm of seven. None of the included trials reported on cannabinoid dependence or psychosis.
According to the European Medicines Agency, P-values are of limited value as relative or absolute differences in terms of adverse effects [113]. A non-significant difference between treatments will not allow for a conclusion on the absence of a difference in safety [113]. In cases of adjustment for multiplicity, the European Medicines Agency state that this can be counterproductive for considerations of safety [113]. Hence, even though meta-analysis and TSA did not show a statistically significant difference when assessing serious adverse events, our results show indications of a harmful effect which should be considered before prescribing cannabinoids for pain.
Our findings are in contrast to the majority of previous reviews which have indicated an adequate analgesic effect of cannabinoids and supported the use of cannabinoids for the treatment of chronic pain [23-26, 114, 115]. Our findings suggest that cannabinoids reduced chronic pain when compared with placebo, however, whether this effect is clinically important seems questionable.
Our findings are in agreement with position statement of the International Association for the Study of Pain (IASP) [116]. IASP have identified important research gaps and due to the lack of high-quality clinical evidence IASP does not currently endorse general use of cannabis and cannabinoids for pain relief [116].
Our findings regarding cancer pain and acute pain are in line with previous reviews on this topic [117][118][119].

Strengths
Our present review has several strengths. Our methodology was predefined and was described in detail in our published protocol [33]. To control the risk of random errors, we used TSA [47] and adjusted our thresholds for statistical significance [46]. We included more trials than any other previous review, which has increased our power and precision and strengthened our analyses. We assessed the risk of bias of all included trials to assess the risks of systematic errors [48,49], and we used our eight-step procedure to assess if the thresholds for statistical and clinical significance were crossed [46]. Furthermore, we predefined MIDs for all outcomes to assess the clinical implications for patients of our results [33]. Pain level thresholds for acute pain and for chronic pain were predefined based on Olsen et al. [120,121]. The MID of one point on NRS is considered lenient in comparison to previous reviews, and our predefined lenient quantification decreases the risk of erroneous rejections of cannabinoids' beneficial effects on pain [23,29]. We were also in contact with several relevant patient associations in Denmark at the protocol stage to select the most relevant patient-important outcomes [33].

Limitations
Our review also has several limitations. All trials except five [60,80,90,111] were at high risk of bias. Therefore, there is a high risk that our results overestimate the beneficial effects and underestimate the harmful effects of cannabinoids [122][123][124][125][126][127][128]. We decided to combine the VAS scores and the NRS scores by converting the results to NRS scores. Even though the two scoring systems correspond very well, some information may be lost in the conversion [129]. Furthermore, a limitation of this systematic review is that we only compared the cannabinoid intervention with placebo. Hence, our results do not assess the effects of cannabinoids compared with other types of analgesics (e.g., opioids).
When conducting a subgroup analysis, one is at risk of study-level confounding because the subgroup analyses are based on aggregate data on a trial level and we did not obtain any individual patient data which may decrease the statistical power of our subgroup analyses. This is a common potential limitation in a meta-analysis of aggregate data.

Minimal important difference
Pain and quality of sleep measurements are subjective measures, why imprecision could be present when assessing these outcomes. We, therefore, need to be careful before dismissing such outcome results as clinically unimportant. Nevertheless, any outcome result should be related to a predefined minimal important difference (MID) to ensure the scientific validity of trial results and to avoid focus on statistically significant results without importance to patients. If a large number of trial participants are randomised, small and clinically irrelevant intervention effects may lead to statistically significant results and rejection of the null hypothesis [130]. Jaeschke et al. defined the MID as 'the smallest difference in score in the domain of interest which patients perceive as beneficial' [131]. Olsen et al. have conducted two systematic reviews on this matter in order to gather the evidence and present an estimate of the MID for pain [120,121]. Olsen et al. conducted a systematic review on the MID in patients with acute pain and concluded that the median of the studies' results was 17 mm on VAS (IQR 14 mm to 23 mm) [120]. Another systematic review conducted by Olsen et al. was on the MID in patients with chronic pain and the results showed a median of 23 mm on VAS (IQR 12 mm to 39 mm) when using the within-patient anchor-based method, while the median in studies using the sensitivity-based and specificity-based method was 20 mm on VAS (IQR 15 mm to 30 mm) [121].
Our MID for quality of sleep was not based on previous studies, because such studies have not been conducted. We, therefore, based our estimation of MID on Cohen's D higher than 0.5 [132]. The 0.5 SMD threshold was originally proposed by Cohen (as a minimum for a 'moderate' effect) and has been used as a MID in several studies across medical specialties [132]. Nevertheless, it has to be considered that the MID estimation for quality of sleep compared to the MID for pain is more unclear because studies assessing the MID are lacking.
Several countries have recently either expanded or introduced the medical use of cannabinoids. Of the many different approaches introduced globally only a few have been presented by the European Monitoring Centre for Drugs and Drug Addiction (EMCDDA) in their report [133]. Canada was one of the first countries to establish a national programme for the medical use of cannabinoids in 1999 and have since evolved to an expanded access programme [134]. New legislation in 2014 licensed more cannabis producers, allowed doctors greater latitude in prescribing, removed federal oversight of prescribing, and permitted patients to receive cannabis directly from licensed producers [135]. Similarly, numerous European countries have allowed the usage of cannabinoids for medical purposes [133]. The different national regulatory frameworks are complicated, but the most common initial approach implemented is to use some form of special access scheme. Examples of countries that have established some form of exceptional use programme or access programme to allow access to cannabinoid preparations for the treatment of pain are Croatia, Denmark, Finland, Norway, Poland, Sweden, Czechia, Germany, Italy, and The Netherlands [133]. According to our present results, the medical use of cannabinoids for pain ought to be reconsidered.
The NASEM report from 2017 on the health effects of marijuana reviewed the evidence on the use of cannabinoids as a treatment for chronic pain [136]. The primary source of information for this summary was based on the works of Whiting et al. suggesting that cannabinoids demonstrate a modest effect on pain [114]. Our present review represents the most comprehensive systematic assessment of the effects of cannabinoids on pain. This systematic review will furthermore work as recommendation for where focus needs to be in future randomised clinical trials.

Conclusions
Cannabinoids reduced chronic pain and improved quality of sleep, but the effect sizes are of questionable importance. Cannabinoids had no effects on acute pain or cancer pain and increased the risk of non-serious adverse events. The harmful effects of cannabinoids for pain seem to outweigh the potential benefits. The expanded medical use of cannabinoids for pain is at this point questionable.